Multifractal Nonlinearity Moderates Feedforward and Feedback Responses to Suprapostural Perturbations

Author:

Kelty-Stephen Damian G.1,Lee Jinhyun2,Cole Keith R.3ORCID,Shields Richard K.2ORCID,Mangalam Madhur4ORCID

Affiliation:

1. Department of Psychology, State University of New York at New Paltz, New Paltz, NY, USA

2. Department of Physical Therapy and Rehabilitation Sciences, University of Iowa, Iowa City, IA, USA

3. Department of Health, Human Function, and Rehabilitation Science, George Washington University, Washington, DC, USA

4. Division of Biomechanics and Research Development, Department of Biomechanics, and Center for Research in Human Movement Variability, University of Nebraska at Omaha, Omaha, NE, USA

Abstract

An adaptive response to unexpected perturbations requires near-term and long-term adjustments over time. We used multifractal analysis to test how nonlinear interactions across timescales might support an adaptive response following an unpredictable perturbation. We reanalyzed torque data from 44 young and 24 older adults who performed a single-leg squat task challenged by an unexpected mechanical perturbation and a secondary visual-cognitive task. We report three findings: (a) multifractal nonlinearity interacted with pre-perturbation torque production and task error to presage greater pre-voluntary feedforward increases and greater voluntary reductions, respectively, in post-perturbation task error; (b) multifractal nonlinearity presaged relatively smaller task error than standard deviations of both pre-perturbation torques and pre-perturbation task error; and (c) increased task demand (e.g., age-related changes in dexterity and dual-task settings) led to multifractal nonlinearity presaging reduced task error. All these results were consistent with our expectations, except that a pre-perturbation knee torque-dependent increase in post-perturbation task error appeared later for older than for younger participants. This correlational multifractal modeling offered theoretical clarity on the possible roles of nonlinear interactions across timescales, moderating both feedforward and feedback processes, and presaging greater stability when the standard deviation is relatively large and task demands are strong. Thus, multifractal nonlinearity usefully describes movement variability even when paired with classical descriptors like the standard deviation. We discuss potential insights from these findings for understanding suprapostural dexterity and developing rehabilitative interventions.

Funder

University of Nebraska at Omaha

Publisher

SAGE Publications

Subject

Sensory Systems,Experimental and Cognitive Psychology

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